Real-time foot clearance and environment estimation based on foot-mounted wearable sensors

The ambulatory gait monitoring systems (AGMS) using wearable devices have a great attention for health monitoring of individuals. Foot clearance is one of gait parameters and an indicator of gait quality and safety. Conventionally, foot clearance is calculated by post-processing using several methods such as extended Kalman filter (EKF), a weighted Fourier linear combiner (WFLC), a simple biomechanical foot model, zero velocity update (ZVU), and optimally filtered direct and reverse integration (OFDRI). However, real-time foot clearance (FC) estimation is required to apply to control of neural prostheses and assistive devices to prevent falling down. In addition, since humans adapt to several environments during gait motion, walking patterns are different among leveled walk, ramp walk, and stair walk. Therefore, environmental recognition also has an important role for the devices. Aim of this study is an implication of a system which performs real-time foot clearance and environment estimation in several situations. Different configurations of infrared (IR) distance sensors are utilized with a foot-mounted inertia measurement unit (IMU: an acceleration sensor, a gyro sensor, a magnetometer, and an air pressure sensor) sensor. Two IR sensors are attached to both sides of a shoe with different orientation. Developed system is tested in case of leveled walk, ramp walk, and stair walk. As the result, the developed system can estimate foot clearance and find characteristics of walking in different gait motion.